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Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to keep pace with this rapidly-advancing field.
About the Author: W. H. Majoros is Staff Scientist at the Center for Bioinformatics and Computational Biology, in the Institute for Genome Sciences and Policy at Duke University. He has worked as a research scientist in the fields of computational biology, natural language processing, and information retrieval for over a decade. He was part of the human genome project at Celera Genomics and has taken part in the sequencing and analysis of numerous organisms including human, mouse, fly and mosquito.
Title: METHODS FOR COMPUTATIONAL GENE PREDICTION
Publisher: Cambridge University Press
Publication Date: 2007
Binding: Soft cover
Condition: Brand New
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Paperback. Condition: Good. The book has been read but remains in clean condition. All pages are intact and the cover is intact. Some minor wear to the spine. Seller Inventory # GOR006514582
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Paperback. Condition: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. Seller Inventory # 0521706947-11-1
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Condition: acceptable. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Acceptable condition! Any other included accessories are also in Acceptable condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear such as cover tears discoloration, staining, marks, scuffs, etc. All pages intact. Seller Inventory # GWSVV.0521706947.A
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